new daily data and new labels for traders

app.py

@@ -95,64 +95,58 @@ def prepare_data():
         .reset_index(name="nr_trades_per_market")
     )
 
-    trader_agents_data = pd.merge(
+    traders_data = pd.merge(
         all_trades, volume_trades_per_trader_and_market, on=["trader_address", "title"]
     )
     daily_info["creation_date"] = daily_info["creation_timestamp"].dt.date
     # adding the trader family column
-    trader_agents_data["trader_family"] = trader_agents_data.apply(
+    traders_data["trader_family"] = traders_data.apply(
         lambda x: get_traders_family(x), axis=1
     )
-    print(trader_agents_data.head())
+    print(traders_data.head())
 
-    trader_agents_data = trader_agents_data.sort_values(
-        by="creation_timestamp", ascending=True
-    )
+    traders_data = traders_data.sort_values(by="creation_timestamp", ascending=True)
 
-    trader_agents_data["month_year_week"] = (
-        trader_agents_data["creation_timestamp"].dt.to_period("W").dt.strftime("%b-%d")
+    traders_data["month_year_week"] = (
+        traders_data["creation_timestamp"].dt.to_period("W").dt.strftime("%b-%d")
     )
 
     closed_markets["month_year_week"] = (
         closed_markets["opening_datetime"].dt.to_period("W").dt.strftime("%b-%d")
     )
-    return trader_agents_data, closed_markets, daily_info
+    return traders_data, closed_markets, daily_info
 
 
-trader_agents_data, closed_markets, daily_info = prepare_data()
+traders_data, closed_markets, daily_info = prepare_data()
 
 demo = gr.Blocks()
 # get weekly metrics by market creator: qs, pearl or all.
 weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
-    trader_agents_data
+    traders_data
 )
 print(
     weekly_metrics_by_market_creator.loc[
         weekly_metrics_by_market_creator["market_creator"] == "all"
     ].roi_diff_perc.describe()
 )
-weekly_agent_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
-    trader_agents_data, trader_filter="agent"
+weekly_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
+    traders_data, trader_filter="non_Olas"
 )
-weekly_non_agent_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
-    trader_agents_data, trader_filter="non_agent"
+weekly_non_olas_metrics_by_market_creator = compute_weekly_metrics_by_market_creator(
+    traders_data, trader_filter="non_Olas"
 )
 
-weekly_winning_metrics = compute_winning_metrics_by_trader(
-    trader_agents_data=trader_agents_data
-)
-weekly_agent_winning_metrics = compute_winning_metrics_by_trader(
-    trader_agents_data=trader_agents_data, trader_filter="agent"
+weekly_winning_metrics = compute_winning_metrics_by_trader(traders_data=traders_data)
+weekly_non_olas_winning_metrics = compute_winning_metrics_by_trader(
+    traders_data=traders_data, trader_filter="non_Olas"
 )
-weekly_non_agent_winning_metrics = compute_winning_metrics_by_trader(
-    trader_agents_data=trader_agents_data, trader_filter="non_agent"
+weekly_non_Olas_winning_metrics = compute_winning_metrics_by_trader(
+    traders_data=traders_data, trader_filter="non_Olas"
 )
 
 with demo:
-    gr.HTML("<h1>Trader agents monitoring dashboard </h1>")
-    gr.Markdown(
-        "This app shows the weekly performance of the trader agents in Olas Predict."
-    )
+    gr.HTML("<h1>Traders monitoring dashboard </h1>")
+    gr.Markdown("This app shows the weekly performance of the traders in Olas Predict.")
 
     with gr.Tabs():
         with gr.TabItem("🔥 Weekly metrics"):
@@ -185,11 +179,11 @@ with demo:
                 inputs=trader_details_selector,
                 outputs=trader_markets_plot,
             )
-            # Agentic traders graph
+
             with gr.Row():
-                gr.Markdown("# Weekly metrics of trader Agents 🤖")
+                gr.Markdown("# Weekly metrics of  🌊 Olas traders")
             with gr.Row():
-                trader_a_details_selector = gr.Dropdown(
+                trader_o_details_selector = gr.Dropdown(
                     label="Select a weekly trader metric",
                     choices=trader_metric_choices,
                     value=default_trader_metric,
@@ -199,7 +193,7 @@ with demo:
                 with gr.Column(scale=3):
                     a_trader_markets_plot = plot_trader_metrics_by_market_creator(
                         metric_name=default_trader_metric,
-                        traders_df=weekly_agent_metrics_by_market_creator,
+                        traders_df=weekly_metrics_by_market_creator,
                     )
                 with gr.Column(scale=1):
                     trade_details_text = get_metrics_text()
@@ -207,18 +201,18 @@ with demo:
             def update_a_trader_details(trader_detail):
                 return plot_trader_metrics_by_market_creator(
                     metric_name=trader_detail,
-                    traders_df=weekly_agent_metrics_by_market_creator,
+                    traders_df=weekly_metrics_by_market_creator,
                 )
 
-            trader_a_details_selector.change(
+            trader_o_details_selector.change(
                 update_a_trader_details,
-                inputs=trader_a_details_selector,
+                inputs=trader_o_details_selector,
                 outputs=a_trader_markets_plot,
             )
 
-            # Non-agentic traders graph
+            # Non-Olas traders graph
             with gr.Row():
-                gr.Markdown("# Weekly metrics of Non-agent traders")
+                gr.Markdown("# Weekly metrics of Non-Olas traders")
             with gr.Row():
                 trader_na_details_selector = gr.Dropdown(
                     label="Select a weekly trader metric",
@@ -230,7 +224,7 @@ with demo:
                 with gr.Column(scale=3):
                     na_trader_markets_plot = plot_trader_metrics_by_market_creator(
                         metric_name=default_trader_metric,
-                        traders_df=weekly_non_agent_metrics_by_market_creator,
+                        traders_df=weekly_non_olas_metrics_by_market_creator,
                     )
                 with gr.Column(scale=1):
                     trade_details_text = get_metrics_text()
@@ -238,7 +232,7 @@ with demo:
             def update_na_trader_details(trader_detail):
                 return plot_trader_metrics_by_market_creator(
                     metric_name=trader_detail,
-                    traders_df=weekly_non_agent_metrics_by_market_creator,
+                    traders_df=weekly_non_olas_metrics_by_market_creator,
                 )
 
             trader_na_details_selector.change(
@@ -247,7 +241,7 @@ with demo:
                 outputs=na_trader_markets_plot,
             )
         with gr.TabItem("📅 Daily metrics"):
-            current_week_trades = get_current_week_data(trades_df=trader_agents_data)
+            current_week_trades = get_current_week_data(trades_df=traders_data)
             live_trades_current_week = get_current_week_data(trades_df=daily_info)
             if len(current_week_trades) > 0:
                 daily_prof_metrics_by_market_creator = (
@@ -291,7 +285,7 @@ with demo:
             )
 
             with gr.Row():
-                gr.Markdown("# Daily live metrics for trader Agents 🤖")
+                gr.Markdown("# Daily live metrics for 🌊 Olas traders")
             with gr.Row():
                 a_trader_live_details_selector = gr.Dropdown(
                     label="Select a daily live metric",
@@ -304,7 +298,7 @@ with demo:
                     a_trader_live_details_plot = plot_daily_metrics(
                         metric_name=default_daily_metric,
                         trades_df=live_metrics_by_market_creator,
-                        trader_filter="agent",
+                        trader_filter="Olas",
                     )
                 with gr.Column(scale=1):
                     trade_details_text = get_metrics_text(daily=True)
@@ -313,7 +307,7 @@ with demo:
                 a_trader_plot = plot_daily_metrics(
                     metric_name=trade_detail,
                     trades_df=live_metrics_by_market_creator,
-                    trader_filter="agent",
+                    trader_filter="Olas",
                 )
                 return a_trader_plot
 
@@ -323,7 +317,7 @@ with demo:
                 outputs=[a_trader_live_details_plot],
             )
             with gr.Row():
-                gr.Markdown("# Daily live metrics for Non-agent traders")
+                gr.Markdown("# Daily live metrics for Non-Olas traders")
             with gr.Row():
                 na_trader_live_details_selector = gr.Dropdown(
                     label="Select a daily live metric",
@@ -336,7 +330,7 @@ with demo:
                     na_trader_live_details_plot = plot_daily_metrics(
                         metric_name=default_daily_metric,
                         trades_df=live_metrics_by_market_creator,
-                        trader_filter="non_agent",
+                        trader_filter="non_Olas",
                     )
                 with gr.Column(scale=1):
                     trade_details_text = get_metrics_text(daily=True)
@@ -347,7 +341,7 @@ with demo:
                 na_trader_plot = plot_daily_metrics(
                     metric_name=trade_detail,
                     trades_df=live_metrics_by_market_creator,
-                    trader_filter="non_agent",
+                    trader_filter="non_Olas",
                 )
                 return na_trader_plot
 
@@ -357,42 +351,6 @@ with demo:
                 outputs=[na_trader_live_details_plot],
             )
 
-            # with gr.Row():
-            #     gr.Markdown("# Daily profitability metrics available for all trades")
-            # if len(current_week_trades) > 0:
-            #     with gr.Row():
-            #         trader_daily_details_selector = gr.Dropdown(
-            #             label="Select a daily trade metric",
-            #             choices=trader_metric_choices,
-            #             value=default_trader_metric,
-            #         )
-
-            #     with gr.Row():
-            #         with gr.Column(scale=3):
-            #             trader_daily_details_plot = plot_daily_metrics(
-            #                 metric_name=default_trader_metric,
-            #                 trades_df=daily_prof_metrics_by_market_creator,
-            #             )
-            #         with gr.Column(scale=1):
-            #             trader_details_text = get_metrics_text(daily=True)
-
-            #     def update_trader_daily_details(
-            #         trade_detail, trader_daily_details_plot
-            #     ):
-            #         new_a_plot = plot_daily_metrics(
-            #             metric_name=trade_detail,
-            #             trades_df=daily_prof_metrics_by_market_creator,
-            #         )
-            #         return new_a_plot
-
-            #     trader_daily_details_selector.change(
-            #         update_trader_daily_details,
-            #         inputs=[trader_daily_details_selector, trader_daily_details_plot],
-            #         outputs=[trader_daily_details_plot],
-            #     )
-            # else:
-            #     gr.Markdown("Data not available yet")
-
         with gr.TabItem("📉 Markets Kullback–Leibler divergence"):
             with gr.Row():
                 gr.Markdown(
@@ -415,7 +373,7 @@ with demo:
                 gr.Markdown("# Weekly total bet amount per trader type for all markets")
             with gr.Row():
                 total_bet_amount = plot_total_bet_amount(
-                    trader_agents_data, market_filter="all"
+                    traders_data, market_filter="all"
                 )
 
             with gr.Row():
@@ -424,7 +382,7 @@ with demo:
                 )
             with gr.Row():
                 a_trader_total_bet_amount = plot_total_bet_amount(
-                    trader_agents_data, market_filter="pearl"
+                    traders_data, market_filter="pearl"
                 )
 
             with gr.Row():
@@ -433,28 +391,26 @@ with demo:
                 )
             with gr.Row():
                 na_trader_total_bet_amount = plot_total_bet_amount(
-                    trader_agents_data, market_filter="quickstart"
+                    traders_data, market_filter="quickstart"
                 )
         with gr.TabItem("💰 Money invested per market"):
             with gr.Row():
                 gr.Markdown("# Weekly bet amounts per market for all traders")
             with gr.Row():
-                bet_amounts = plot_total_bet_amount_per_trader_per_market(
-                    trader_agents_data
-                )
+                bet_amounts = plot_total_bet_amount_per_trader_per_market(traders_data)
 
             with gr.Row():
-                gr.Markdown("# Weekly bet amounts per market for traders Agents 🤖")
+                gr.Markdown("# Weekly bet amounts per market for 🌊 Olas traders")
             with gr.Row():
                 a_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
-                    trader_agents_data, trader_filter="agent"
+                    traders_data, trader_filter="Olas"
                 )
 
             with gr.Row():
-                gr.Markdown("# Weekly bet amounts per market for Non-agent traders")
+                gr.Markdown("# Weekly bet amounts per market for Non-Olas traders")
             with gr.Row():
                 na_trader_bet_amounts = plot_total_bet_amount_per_trader_per_market(
-                    trader_agents_data, trader_filter="non_agent"
+                    traders_data, trader_filter="non_Olas"
                 )
 
         with gr.TabItem("🎖️Weekly winning trades % per trader"):
@@ -465,24 +421,21 @@ with demo:
             with gr.Row():
                 winning_metric = plot_winning_metric_per_trader(weekly_winning_metrics)
 
-            # Agentic traders
             with gr.Row():
-                gr.Markdown("# Weekly winning trades percentage from traders Agents")
+                gr.Markdown("# Weekly winning trades percentage from 🌊 Olas traders")
             with gr.Row():
                 metrics_text = get_metrics_text()
             with gr.Row():
-                winning_metric = plot_winning_metric_per_trader(
-                    weekly_agent_winning_metrics
-                )
+                winning_metric = plot_winning_metric_per_trader(weekly_winning_metrics)
 
-            # Non_agentic traders
+            # non_Olasic traders
             with gr.Row():
-                gr.Markdown("# Weekly winning trades percentage from Non-agent traders")
+                gr.Markdown("# Weekly winning trades percentage from Non-Olas traders")
             with gr.Row():
                 metrics_text = get_metrics_text()
             with gr.Row():
                 winning_metric = plot_winning_metric_per_trader(
-                    weekly_non_agent_winning_metrics
+                    weekly_non_Olas_winning_metrics
                 )
 
 demo.queue(default_concurrency_limit=40).launch()

scripts/metrics.py

@@ -168,29 +168,27 @@ def win_metrics_trader_level(weekly_data):
 
 
 def compute_weekly_metrics_by_market_creator(
-    trader_agents_data: pd.DataFrame, trader_filter: str = None
+    traders_data: pd.DataFrame, trader_filter: str = None
 ) -> pd.DataFrame:
     """Function to compute the metrics at the trader level per week
     and with different categories by market creator"""
     contents = []
-    all_weeks = list(trader_agents_data.month_year_week.unique())
+    all_weeks = list(traders_data.month_year_week.unique())
     for week in all_weeks:
-        weekly_data = trader_agents_data.loc[
-            trader_agents_data["month_year_week"] == week
-        ]
+        weekly_data = traders_data.loc[traders_data["month_year_week"] == week]
         print(f"Computing weekly metrics for week ={week} by market creator")
-        # traverse each trader agent
+        # traverse each trader
         traders = list(weekly_data.trader_address.unique())
         for trader in tqdm(traders, desc=f"Trader' metrics", unit="metrics"):
             if trader_filter is None:
                 contents.append(merge_trader_weekly_metrics(trader, weekly_data, week))
             elif trader_filter == "agent":
-                filtered_data = weekly_data.loc[weekly_data["staking"] != "non_agent"]
+                filtered_data = weekly_data.loc[weekly_data["staking"] != "non_Olas"]
                 contents.append(
                     merge_trader_weekly_metrics(trader, filtered_data, week)
                 )
-            else:  # non_agent traders
-                filtered_data = weekly_data.loc[weekly_data["staking"] == "non_agent"]
+            else:  # non_Olas traders
+                filtered_data = weekly_data.loc[weekly_data["staking"] == "non_Olas"]
                 contents.append(
                     merge_trader_weekly_metrics(trader, filtered_data, week)
                 )
@@ -200,7 +198,7 @@ def compute_weekly_metrics_by_market_creator(
 
 
 def compute_daily_metrics_by_market_creator(
-    trader_agents_data: pd.DataFrame,
+    traders_data: pd.DataFrame,
     trader_filter: str = None,
     live_metrics: bool = False,
 ) -> pd.DataFrame:
@@ -208,11 +206,11 @@ def compute_daily_metrics_by_market_creator(
     and with different categories by market creator"""
     contents = []
 
-    all_days = list(trader_agents_data.creation_date.unique())
+    all_days = list(traders_data.creation_date.unique())
     for day in all_days:
-        daily_data = trader_agents_data.loc[trader_agents_data["creation_date"] == day]
+        daily_data = traders_data.loc[traders_data["creation_date"] == day]
         print(f"Computing daily metrics for {day}")
-        # traverse each trader agent
+        # traverse each trader
         traders = list(daily_data.trader_address.unique())
         for trader in tqdm(traders, desc=f"Trader' daily metrics", unit="metrics"):
             if trader_filter is None:
@@ -220,12 +218,12 @@ def compute_daily_metrics_by_market_creator(
                     merge_trader_daily_metrics(trader, daily_data, day, live_metrics)
                 )
             elif trader_filter == "agentic":
-                filtered_data = daily_data.loc[daily_data["staking"] != "non_agent"]
+                filtered_data = daily_data.loc[daily_data["staking"] != "non_Olas"]
                 contents.append(
                     merge_trader_daily_metrics(trader, filtered_data, day, live_metrics)
                 )
-            else:  # non_agent traders
-                filtered_data = daily_data.loc[daily_data["staking"] == "non_agent"]
+            else:  # non_Olas traders
+                filtered_data = daily_data.loc[daily_data["staking"] == "non_Olas"]
                 contents.append(
                     merge_trader_daily_metrics(trader, filtered_data, day, live_metrics)
                 )
@@ -235,20 +233,20 @@ def compute_daily_metrics_by_market_creator(
 
 
 def compute_winning_metrics_by_trader(
-    trader_agents_data: pd.DataFrame, trader_filter: str = None
+    traders_data: pd.DataFrame, trader_filter: str = None
 ) -> pd.DataFrame:
     """Function to compute the winning metrics at the trader level per week and with different market creators"""
-    market_all = trader_agents_data.copy(deep=True)
+    market_all = traders_data.copy(deep=True)
     market_all["market_creator"] = "all"
 
     # merging both dataframes
-    final_traders = pd.concat([market_all, trader_agents_data], ignore_index=True)
+    final_traders = pd.concat([market_all, traders_data], ignore_index=True)
     final_traders = final_traders.sort_values(by="creation_timestamp", ascending=True)
 
     if trader_filter == "agentic":
-        final_traders = final_traders.loc[final_traders["staking"] != "non_agent"]
-    else:  # non_agent traders
-        final_traders = final_traders.loc[final_traders["staking"] == "non_agent"]
+        final_traders = final_traders.loc[final_traders["staking"] != "non_Olas"]
+    else:  # non_Olas traders
+        final_traders = final_traders.loc[final_traders["staking"] == "non_Olas"]
 
     winning_df = win_metrics_trader_level(final_traders)
     winning_df.head()